MS, exercise, and the potential for older adults
Bibliographic record
Abstract
Abstract Multiple Sclerosis (MS) is an autoimmune disorder of the central nervous system. The average onset of the disease is 30 years of age, and it afflicts women more often than men (ratio of approximately 2:1). The symptoms of the disease include fatigue, motor weakness, heat sensitivity, reduced mobility, abnormal gait mechanics, and poor balance. These symptoms decrease cognitive and physical functional capacity of an individual and tend to result in sedentary lifestyle behaviors. A sedentary lifestyle among individuals with MS increases the risk of secondary diseases such as coronary heart disease and obesity, particularly as one ages. The effect of exercise in treating symptoms of MS has been under explored, perhaps due to the fact that exercise was thought to magnify MS-related fatigue and other symptoms. Recent research has challenged this notion, advocating exercise as an effective therapy for the management of MS, as well as maintaining overall fitness and improving quality-of-life measures. While the research shows clear benefits, the barriers to exercise participation among MS patients are significant. Recommendations for various forms of exercise are provided, along with strategies for overcoming barriers to participation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".